Mark J Stoutjesdijk

Radboud University Medical Centre (Radboudumc), Nymegen, Gelderland, Netherlands

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Publications (7)82.27 Total impact

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    ABSTRACT: To evaluate automatic characterization of a breast MR lesion by its spatially coherent region of interest (ROI). The method delineated 247 enhancing lesions using Otsu thresholding after manually placing a sphere. Mean Shift Clustering subdivided each volume, based on features including pharmacokinetic parameters. An iteratively trained classifier to predict the most suspicious ROI (IsR) was used, to predict the malignancy likelihood of each lesion. Performance was evaluated using receiver operator characteristic (ROC) analysis, and compared with a previous prototype. IsR was compared with noniterative training. The effect of adding BI-RADS™ morphology (from a radiologist) to the classifier was investigated. The area under the ROC curve (AUC) was 0.83 (95% confidence interval [CI] of 0.77-0.88), and was 0.75 (95%CI = 0.68-0.81; P = 0.029) without pharmacokinetic features. IsR performed better than conventional selection, based on one feature (AUC 0.75, 95%CI = 0.68-0.81; P = 0.035). With morphology, the AUC was 0.84 (95%CI = 0.78-0.88) versus 0.82 without (P = 0.40). Breast lesions can be characterized by their most suspicious, contiguous ROI using multi-feature clustering and iterative training. Characterization was improved by including pharmacokinetic modeling, while in our experiments, including morphology did not improve characterization. J. Magn. Reson. Imaging 2012;36:1104-1112. © 2012 Wiley Periodicals, Inc.
    Journal of Magnetic Resonance Imaging 07/2012; 36(5):1104-12. · 2.57 Impact Factor
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    ABSTRACT: The value of pharmacokinetic parameters derived from fast dynamic imaging during initial enhancement in characterizing breast lesions on magnetic resonance imaging (MRI) was evaluated. Sixty-eight malignant and 34 benign lesions were included. In the scanning protocol, high temporal resolution imaging was combined with high spatial resolution imaging. The high temporal resolution images were recorded every 4.1 s during initial enhancement (fast dynamic analysis). The high spatial resolution images were recorded at a temporal resolution of 86 s (slow dynamic analysis). In the fast dynamic evaluation pharmacokinetic parameters (K(trans), V(e) and k(ep)) were evaluated. In the slow dynamic analysis, each lesion was scored according to the BI-RADS classification. Two readers evaluated all data prospectively. ROC and multivariate analysis were performed. The slow dynamic analysis resulted in an AUC of 0.85 and 0.83, respectively. The fast dynamic analysis resulted in an AUC of 0.83 in both readers. The combination of both the slow and fast dynamic analyses resulted in a significant improvement of diagnostic performance with an AUC of 0.93 and 0.90 (P = 0.02). The increased diagnostic performance found when combining both methods demonstrates the additional value of our method in further improving the diagnostic performance of breast MRI.
    European Radiology 07/2008; 18(6):1123-33. · 4.34 Impact Factor
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    ABSTRACT: To evaluate a new method for automated determination of a region of interest (ROI) for the analysis of contrast enhancement in breast MRI. Mean shift multidimensional clustering (MS-MDC) was employed to divide 92 lesions into several spatially contiguous clusters each, based on multiple enhancement parameters. The ROIs were defined as the clusters with the highest probability of malignancy. The performance of enhancement analysis within these ROIs was estimated using the area under the receiver operator characteristic curve (AUC), and compared against a radiologist's final assessment and a classifier using histogram analysis (HA). For HA, the first, second, and third quartiles were evaluated. MS-MDC resulted in AUC = 0.88 with a 95% confidence interval (CI) of 0.81-0.95. The AUC for the radiologist's assessment was 0.93 (95%CI = 0.87-0.97). Best HA performance was found using the first quartile, with AUC = 0.79 (95%CI = 0.69-0.88). There was no significant difference between MS-MDC and the radiologist (P = 0.40). The improvement of MS-MDC over HA was significant (P = 0.018). Mean shift clustering followed by automated selection of the most suspicious cluster resulted in accurate ROIs in breast MRI lesions.
    Journal of Magnetic Resonance Imaging 10/2007; 26(3):606-14. · 2.57 Impact Factor
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    ABSTRACT: The objective of this study was to evaluate the interobserver variability in reporting descriptive kinetic and morphologic enhancement features at breast magnetic resonance imaging. Four observers evaluated 103 lesions, 49 malignant and 54 benign, proven by histopathology. They used standardized terminology with the following characteristics: "early enhancement kinetics" and "late enhancement kinetics" in curves from both reader-determined and preset regions of interest (ROIs), "enhancement pattern," "shape," "margin," "internal enhancement," and a final assessment score. Agreement was calculated using the kappa statistic. Differences in agreement were calculated using Fisher exact test. kappa was 0.27 for both early and late enhancement; preset ROIs improved kappa to 0.47 and 0.67, respectively (odds ratios, 1.7 and 4.5). kappa was 0.45 for pattern, 0.42 for shape, 0.26 for margin, 0.25 for internal enhancement, and 0.28 for final assessment. There was considerable variability in the use of most generally accepted terms. The preparation of ROIs was a major source of variability in the interpretation of enhancement curves.
    Investigative Radiology 07/2005; 40(6):355-62. · 5.46 Impact Factor
  • M J Stoutjesdijk, J O Barentsz
    New England Journal of Medicine 12/2001; 345(20):1499; author reply 1499-500. · 51.66 Impact Factor
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    ABSTRACT: Although breast cancer screening is recommended to start at a younger age for women with a hereditary risk of breast cancer, the sensitivity of mammography for these women is reduced. We compared magnetic resonance imaging (MRI) with mammography to determine which is more sensitive and whether MRI could play a role in the early detection of breast cancer for these women. We constructed a retrospective cohort of all breast MRI and mammography surveillance reports made in our department from November 1994 to February 2001. All of the 179 women in the cohort had received biannual palpation in addition to annual imaging by MRI, mammography, or both. The 258 MRI images and the 262 mammograms were classified with the use of the BI-RADS (i.e., Breast Imaging Reporting and Data System) scoring system, which has five categories to indicate the level of suspicion of a lesion. Receiver operator characteristic curves were generated for MRI and mammography, and the area under each curve (AUC) was assessed for the entire cohort of 179 women and for a subset of 75 women who had received both an MRI and a mammographic examination within a 4-month period. All statistical tests were two-sided. In the cohort of 179 women, we detected 13 breast cancers. Seven cancers were not revealed by mammography, but all were detected by MRI. For the entire cohort, the AUC for mammography was 0.74 (95% confidence interval [CI] = 0.68 to 0.79), and the AUC for MRI was 0.99 (95% CI = 0.98 to 1.0). For the subset of women who had both examinations, the AUC for mammography was 0.70 (95% CI = 0.60 to 0.80), and the AUC for MRI was 0.98 (95% CI = 0.95 to 1.0). MRI was more accurate than mammography in annual breast cancer surveillance of women with a hereditary risk of breast cancer. Larger prospective studies to examine the role of MRI in screening programs are justified.
    JNCI Journal of the National Cancer Institute 08/2001; 93(14):1095-102. · 14.34 Impact Factor
  • C Boetes, M Stoutjesdijk
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    ABSTRACT: Hereditary breast cancer accounts for 5% to 10% of the total breast cancer burden. Screening of this group of women has been done by palpation and conventional mammography until recently, but because of the age group, mammography has a limited value. MR mammography has been demonstrated to be a reliable imaging modality in this group of patients.
    Magnetic Resonance Imaging Clinics of North America 06/2001; 9(2):357-72, vii. · 1.34 Impact Factor

Publication Stats

264 Citations
82.27 Total Impact Points

Institutions

  • 2007
    • Radboud University Medical Centre (Radboudumc)
      • Department of Human Genetics
      Nymegen, Gelderland, Netherlands
  • 2001–2007
    • Radboud University Nijmegen
      • Department of Radiology
      Nijmegen, Provincie Gelderland, Netherlands